Large-scale multivariate dataset on the characterization of microbiota diversity, microbial growth dynamics, metabolic spoilage volatilome and sensorial profiles of two industrially produced meat products subjected to changes in lactate concentration and

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Large-scale multivariate dataset on the characterization of microbiota diversity, microbial growth dynamics, metabolic spoilage volatilome and sensorial profiles of two industrially produced meat products subjected to

changes in lactate concentration and packaging atmosphere

Simon Poirier, Ngoc-Du Martin Luong, Valérie Anthoine, Sandrine Guillou, Jeanne-Marie Membré, Nicolas Moriceau, Sandrine Reze, Monique Zagorec,

Carole Feurer, Bastien Fremaux, et al.

To cite this version:

Simon Poirier, Ngoc-Du Martin Luong, Valérie Anthoine, Sandrine Guillou, Jeanne-Marie Membré,

et al.. Large-scale multivariate dataset on the characterization of microbiota diversity, microbial

growth dynamics, metabolic spoilage volatilome and sensorial profiles of two industrially produced

meat products subjected to changes in lactate concentration and packaging atmosphere. Data in

Brief, Elsevier, 2020, 30, pp.1-8. �10.1016/j.dib.2020.105453�. �hal-02914971�

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ContentslistsavailableatScienceDirect

Data in Brief

journalhomepage:www.elsevier.com/locate/dib

Data Article

Large-scale multivariate dataset on the characterization of microbiota diversity, microbial growth dynamics, metabolic

spoilage volatilome and sensorial proﬁles of two industrially produced meat products subjected to changes in lactate concentration and packaging atmosphere

Simon Poirier

^a^,¹

, Ngoc-Du Martin Luong

^b^,¹

, Valérie Anthoine

^b

, Sandrine Guillou

^b

, Jeanne-Marie Membré

^b

, Nicolas Moriceau

^b

, Sandrine Rezé

^b

, Monique Zagorec

^b

, Carole Feurer

^c

,

Bastien Frémaux

^c

, Sabine Jeuge

^c

, Emeline Robieu

^c

, Marie Champomier-Vergès

^a

, Gwendoline Coeuret

^a

,

Emilie Cauchie

^d

, Georges Daube

^d

, Nicolas Korsak

^d

, Louis Coroller

^e

, Noémie Desriac

^e

, Marie-Hélène Desmonts

^f

, Rodérick Gohier

^f

, Dalal Werner

^f

, Valentin Loux

^g^,^j

, Olivier Rué

^g^,^j

,

Marie-Hélène Dohollou

^h

, Tatiana Defosse

ⁱ

, Stéphane Chaillou

^a^,^∗

aINRAE, AgroParisTech, Micalis Institute, Université Paris-Saclay, 78350, Jouy-en-Josas, France

bINRAE, UMR1014 Secalim, Oniris, Nantes, France

cIFIP-Institut du Porc, Maisons-Alfort et Le Rheu, France

dVeterinary Medicine Faculty, Food Sciences, Université de Liège, FARAH, 40 0 0 Liège, Belgium

eUniversité de Bretagne Occidentale, EA3882 Lubem, Quimper, France

fAerial, 67412 Illkirch, France

gINRAE, MaIAGE, Université Paris-Saclay, 78350 Jouy-en-Josas, France

hCooperl, 22403 Lamballe, Armor, France

iCellule Recherche et Innovation, Groupe LDC, Sablé sur Sarthe, France

jINRAE, BioinfOmics, MIGALE bioinformatics facility, Université Paris-Saclay, 78350 Jouy-en-Josas, France

∗ Corresponding author.

E-mail address: stephane.chaillou@inrae.fr (S. Chaillou).

1These authors contributed equally as ﬁrst authors to this work.

https://doi.org/10.1016/j.dib.2020.105453

( http://creativecommons.org/licenses/by/4.0/ )

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2 S. Poirier, N.-D.M. Luong and V. Anthoine et al. / Data in Brief 30 (2020) 105453

a r t i c l e i n f o

Article history:

Received 10 February 2020 Revised 9 March 2020 Accepted 12 March 2020 Available online 20 March 2020 Keywords:

Meat spoilage Food microbiota Microbial ecology Metabolomic Metagenetic

a b s t r a c t

Data inthisarticle providedetailedinformation onthedi- versity of bacterial communities present on 576 samples of raw pork or poultry sausages produced industrially in 2017. Bacterial growth dynamics and diversity were monitored throughout the refrigerated storage period to estimate the impact of packaging atmosphere and the use of potassiumlactateaschemicalpreservative.Thedatainclude severaltypesofanalysis aimingatprovidingacomprehen- sive microbial ecology of spoilageduring storageand how the processparameters doinfluence thisphenomenon.The analysis includes: the gas content in packaging, pH, chro- mametricmeasurements,platecounts(totalmesophilicaer- obic flora and lactic acid bacteria), sensorial properties of theproducts,meta-metabolomicquantificationofvolatileor- ganiccompoundsandbacterialcommunitymetageneticanal- ysis. Bacterial diversity was monitored using two types of ampliconsequencing(16SrRNAandGyrBencodinggenes)at different timepointsforthedifferentconditions (576sam- ples for gyrBand 436 samples for 16S rDNA). Sequencing dataweregeneratedbyusingIlluminaMiSeq.Thesequenc- ingdatahavebeendepositedinthebioprojectPRJNA522361.

Samples accession numbers vary from SAMN10964863 to SAMN10965438forgyrBampliconandfromSAMN10970131 toSAMN10970566for16S.

ThisisanopenaccessarticleundertheCCBYlicense.

(http://creativecommons.org/licenses/by/4.0/)

Speciﬁcationstable

Subject area Applied Microbiology and Biotechnology

More speciﬁc subject area Microbial ecology of food spoilage during industrial production.

Type of data Table, ﬁgure, raw sequencing data

How data was acquired Total aerobic mesophilic population was estimated on Plate Count Agar (PCA) (Oxoid, France) for pork, (Biomerieux, France) for poultry and on de Man, Rogosa, and Sharpe (MRS) agar (Oxoid, France) for pork, (Biomerieux, France) for poultry. Both media were incubated aerobically for 48 h at 30 °C to estimate the bacterial population size in CFU. g ⁻¹of meat. Gas composition of the trays was assessed for all trays with CheckMate3 (Dansensor, France) or Oxybaby O 2/CO 2analyzer (WITT, Germany) for pork and poultry sausages, respectively. The pH of sausages was measured using FiveGo FG2 with the electrode LE427-S7 (Mettler toledo, USA). Color (L ^∗, a ^∗, b ^∗) was assessed using the Minolta CR400 ChromaMeter (Grosseron, France) in CIE-Lab scale. Volatile organic compounds (VOC) were determined by HS–GC–MS on a Varian 450 gas chromatograph (Varian, USA) coupled to a Varian 225-IT mass spectrometer (Varian), equipped with a CTC Combi PAL (CTC Analytics AG, Switzerland). Quantitative descriptive analysis (QDA) was performed using seven olfactory attributes by a trained sensory panel of 15 experts. DNA amplicon sequencing was carried out with Illumina MiSeq.

( continued on next page )

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Data format Raw, analyzed

Parameters for data collection The type of meat used for production of sausage was the ﬁrst parameter analyzed (raw pork sausages and raw poultry sausages). The second parameter was the time of storage from the raw meat material up to sausages at the end of storage (primary cuts, gut casing, spices and fat).

The third parameter was meat batch variability along ten sampling campaigns which were conducted for each meat product. Finally, we analyzed two process parameters: one was the inﬂuence of three doses of potassium lactate (complete dose, half dose or zero dose) used as preservative as well as three packaging atmospheres (air, and two modiﬁed atmospheres i.e. 70%O 2/30%CO 2and 50%N 2/50%CO 2,).

Description of data collection Meat samples were collected directly in two independent factories in France, just out of the production line. The large-scale sampling strategy was organized over a period of six months from July to December 2017.

Data source location Samples related to pork sausages were collected in Lamballe (France, latitude: 48.4667, longitude: −2.5167) while samples related to poultry sausages were collected in Sablé-sur-Sarthe (France, latitude: 47.8376, longitude: −0.3329).

Data accessibility Data are available as supplementary tables (Excel spreadsheets) at the institutional INRAE data repository: https://doi.org/10.15454/UDQLGE . The sequencing data have been deposited in the bioproject PRJNA522361.

Valueofthedata

• Thedataprovidealinkbetweenmeatspoilage(bacterialcounts,pH,color,volatilemetabolic spoilagecompounds non-targetedquantiﬁcationfurther referredas“volatilome” andsenso- rialproﬁles),thepackagingatmosphere,andtheuseoflactateandmicrobiotacomposition.

• Sequencing data can be used to understand the variation of bacterialcommunity dynamics,abundanceanddiversityinthesetwomeatproductsaccordingtothetypeofmeatand packagingatmosphere,andtheuseoflactate.

• Sequencing datacan be usedto identify biomarkers of spoilage.Accessibility to 16S rDNA andgyrB OTU (Operational Taxonomic Unit) dataand detailedassociated metadata allows researcherstoperformnewanalyseswiththeirownresearchpurposes.

• Tenindependentsamplingcampaignswere conductedfortwomeatproducts.Awidenum- ber of conditions were tested (three lactate concentrations and three packaging atmospheres).Thislarge-scale samplingstrategy inwhich over550sampleswere sequenced,at fourdifferent time points(fromday 0to day22 ofstorage) provides aunique dataset for powerfulstatisticalanalysisofprocessparametersinﬂuencingrawmeatsausagespoilage.

1. Datadescription

In the EU 20% of the initial meat production is lost, more than half occurring at animal production, slaughtering, processing and distribution steps [1,2]. This crucial economic and environmental issueinfoodindustry isin partattributedtospoilage duringstorage,whichis the consequence ofbacterial growthand subsequentmetabolic activities causingorganoleptic changes of the ﬁnal product unacceptable forhuman consumption (defects in texture, color, odor,tasteoraspect)[3].

Forindustrialmeatproducers,predictingaccurateused-by-datesfortheirproductsbasedon spoilageoccurrenceremains abigchallenge.Thelackoflarge-scalemultivariatedatagenerated andassociatedwithspeciﬁcmeatproductionsisone ofthegapsthatneeds tobeﬁlledbefore suchchallengecouldbeovercome.Theobjectiveofthisprojectwasthustoprovidesuchdataset based on a large collaborative project betweenacademic partners, technical centers,and two industrial producers. Wecollected overa sixmonths productionperiod, muchcomprehensive information on thedynamics ofbacterial communities andphysico-chemical variables associ-

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4 S. Poirier, N.-D.M. Luong and V. Anthoine et al. / Data in Brief 30 (2020) 105453

T_{0 =Day 2}

n=3 n=9 n=9 n=9

Sausages x3 Lactate doses

x3 Packagings

T_{1 = Day 7}

•Primal cuts

•Spices

•Gut casing

•Fat

T_{i = Day 0}

T_{2 = Day 15}

x3 Packagings

T_{3 = Day 22}

x3 Packagings

34 samples x 10 sampling campaigns x 2 meat product (poultry and pork) Meat Baer

x3 Lactate doses

Embossing and packaging

Poultry factory

INDUSTRIAL PRODUCTION

Pork factory

STORAGE AT 4°C AND 8°C

•Primal cuts

•Spices

•Gut casing

•Fat Meat baer x3 Lactate doses

n=4 (one of each)

pH, Packaging gas composion, Chromametry Enumeraon (Total aerobic mesophilic, Lacc acid bacteria)

Microbial DNA extracon

SHIPMENT AND FREEZING OF SAMPLES SHIPMENT AND

FREEZING OF DNA Microbiota analysis (amplicon sequencing 16S rDNA gyrB)

Meta-Omic data integraon

Sensory analysis Non-targeted metabolic

Volalome analysis

SHIPMENT 4°CSEIROTAROBALLACINHCET&CIMEDACAOT

Fig. 1. Large-scale strategy for the analysis of meat sausage samples and production of the dataset.

atedwithmeatspoilagealongtheprocessingsteps.Processedporkandpoultrymeat(sausages) were chosen as two examples of spoilage sensitive meat products that are among the most consumed in France. Products included all sausages ingredients (meat cuts, gut casing, spice mixes,andfat)tocoverthewholemeatprocess.Theexperimentalworkconsistedindetermin- ingthediversityandthedynamicsofbacterialcommunitiesduringfoodprocessingandstorage, andcorrelatingthem withspoilage occurrence.Inthe frameof thisproject,sensoryandnon- targetedmetabolicvolatilomeanalyseswereperformedinordertocharacterizethemeatprod- uctspoilageinrelationwithfoodprocessingfactorslikeconcentrationofchemicalpreservatives (potassiumlactate)andgascompositionofstoragepackaging.Theoriginalityofthisprojectwas to integrate biotic (microbialecology), abiotic (sensory attributes andstorage conditions) and temporal factors (monitoring along processing steps) to generate heterogeneous multivariate dataforused-by-date predictivemathematical models.Fig. 1illustrates theglobalexperimen- tal designof thisstudy. Links tosupplementary data(available asspreadsheets) presented in Table1includeall themetadatacharacterizingeach sample,aswell asthe samplesthatwere selectedforthedifferentanalyses(16SrDNAsequencing,gyrBsequencing,volatilomeandsen- sorialproﬁle).

2. Experimentaldesign,materialsandmethods 2.1. Experimentaldesignandsampling

The project focused on the monitoring of two food matrices: pork sausages and poultry sausages.Forpork sausages, two typesofmeat pieces were used: normalmid shoulder meat anddefatted/boneless/derindedshoulder meat(also named shoulder4D). Forpoultrysausage, the meat was from turkey. In both sausages, pork fat was added to a ﬁnal content of 20%

and 11% in pork and poultry sausages, respectively. The following additives were added in

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Table 1

List of supplementary tables (Tables available as spreadsheets at https://doi.org/10.15454/UDQLGE ) making up the dataset.

Table S1 Sample nomenclature and metadata associated with each sample.

Table S2 pH dynamics over time for the different meat products.

Table S3 Chromametric measures for the different meat products.

Table S4 Gas composition (%) of the packaging atmosphere over time for the different meat products Table S5 Total mesophilic aerobic ﬂora (log 10CFU. g ⁻¹) over time for the different meat products Table S6 Lactic acid bacteria (log 10CFU. g ⁻¹) over time for the different meat products

Table S7 Non-targeted metabolic volatilome composition (reduced centered normalization of pic areas) over time for the different meat products

Table S8 Sensorial proﬁles over time for the different meat products

Table S9 Microbial diversity analysis based on 16S rDNA V3-V4 region amplicon sequencing including OTU abundance table, OTU taxonomic assignment table and samples metadata table usable for phyloseq R package analysis [4] .

Table S10 Microbial diversity analysis based on gyrB amplicon sequencing including OTU abundance table, OTU taxonomic assignment table and samples metadata table usable for phyloseq R package analysis [4] .

pork sausages: potassium lactate(1.13% w/w, corresponding to full normal dose); sodium ac- etate 0.27%(w/w); sodiumascorbate0.06% (w/w). In poultrysausagesthe followingadditives wereadded:potassiumlactate(2.0%w/w,correspondingtofullnormaldose).Furthermore,both sausages werebattered withaspicemix asingredientaddedto aconcentration of∼2.5% and containing(sodiumsalt∼40%,dextrose ∼10%, spices ∼15%, aromas∼22%).Tensamplingcam- paignswereconductedduring6monthsontheproductionchainsoftwosausageproducersin order to get a suﬃcient number ofindependent biological replicates. For each campaign and each foodmatrix, identicalsamplingstrategy was applied.Four typesof samplescorrespond- ing to the ingredients constituting sausages were collected: primal cuts, gut casing, fat and spices.

Three meat batters were separately prepared with different doses of lactate (the normal dose routinely used by the industrials, half of this dose and without any lactate). The three meat batters were sampled before their embossing into the tubular gut casing. Pork sausages were packedimmediately after embossing whereas poultry sausages were packed 2 days later. Sausages were separately packagedby five into trays under three different atmospheres(normalair;50%CO₂-50%N₂;and70%O₂-30%N₂),sealedwiththinhighbarrierpolyester- basedfilm PET/EVOH (Co-polymerof EthyleneandVinyl alcohol)/PE(PolyEthylene) andstored during the first 5 days at 4°C and then until the end of the incubation at 8°C. The phys- ical properties of the packaging were as follows: oxygen transmission rate <5 cm³/m²·24 h⁻¹·bar⁻¹, CO₂ transmission rate <25 cm³/m². During storage, sausages were sampled at three differentdates: day 7,day15, andday 22(which wasconsidered as an abusedstorage time).

Trayswerefrozenat−20°Cpriorcolor,sensory,andVOCanalyses.Othertreatmentsoranal- yseswereperformeddirectly.

2.2. Physico-chemicalanalyses

Forall samplespH measureswere performedonthree sausagesper trayusingFiveGo FG2 withthe electrodeLE427-S7 (Mettler toledo,USA) insertedin sausages.Forpork sausagesgas composition of each tray was assessed with CheckMate3 (Dansensor, France). The same pro- cedure wasapplied for poultrysausages with a digital O₂/CO₂ Oxybaby analyzer (WITT,Ger- many).Visualcolorchangeswereevaluatedintriplicatesforeachcondition,eachsamplingtime andeach production batchusing theMinolta CR400ChromaMeter (Grosseron,France) in CIE- Labscale.ThemeasurementsdeterminedchromaticcoordinatesofL^∗(brightness),a^∗(green-red balance)andb^∗(blue-yellowbalance).

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6 S. Poirier, N.-D.M. Luong and V. Anthoine et al. / Data in Brief 30 (2020) 105453 2.3.Bacterialcollection

Ten to ﬁfty grams of each food-product batch were mixedin a 400ml stomacher bag of 280μm (Interscience BagPage, France) with 4 vol (40 to 200mL) of BK018HA peptone water (Biokar Diagnostics, France) supplemented with 1% V/V Tween 80 (VWR Chemicals, France).

Mixes were treated for 3min (pork) or 2min (poultry) in a Masticator Homogenizator (IUL, Spain).Then, 32mL of theshreds were collectedandcentrifuged at 500×g for 3minat 4°C tospindownthefoodmatrixﬁbersanddebris.Thestill-turbidsupernatant(∼25mL)wascol- lectedandcentrifugedat3000×g(pork)or10,000xg(poultry)for5minat4°Ctospindown thebacterial cells. The bacterialpellet thus obtainedwaswashed in 1mL ofsterile ultrapure water andcollected after centrifugation as above for 5min at 4°C to serve directly for DNA extractionorforplating.

3. Plating

Bacterialcounts were estimated fromﬁltrates obtained after thestomaching step andfol- lowing the ISO 4833-1:2013 and ISO 15214:1998 methods. Serial dilutions in peptone water were performedand plated on Plate CountAgar (PCA)(Oxoid, France) for pork, (Biomerieux, France) for poultryand on de Man, Rogosa, and Sharpe (MRS)agar (Oxoid,France) forpork, (Biomerieux,France)forpoultryandincubatedaerobicallyfor48hat30°Ctoestimatethetotal aerobicmesophilicpopulationandthemesophiliclacticacidbacteriapopulationsizeinCFUg⁻¹ ofmeat,respectively.

3.1. DNAextraction,ampliﬁcationandsequencing

Total DNA was extracted from bacterial pellets obtained after stomaching and a centrifugation steps using DNeasy PowerFood Microbial Kit (Mobio Laboratories, USA) accord- ing to the manufacturer’s instructions and as described in Poirier et al. [5]. DNA extracts were used forthe ampliﬁcation of the bacterialhypervariable region V3–V4of the 16S rRNA gene withthe primers V3F(5-ACGGRAGGCWGCAGT-3) andV4R (5-TACCAGGGTATCTAATCCT- 3). In parallel,the degeneratedprimers F64 (5-MGNCCNGSNATGTAYATHGG-3) andR353 (5- CNCCRTGNARDCCDCCNGA-3)wereusedtoamplifya∼280-bpregionofgyrBgeneasdescribed inPoirieret al.[5]. Sequencingwasperformed byGenoscreen (France) onIllumina Miseq se- quencerusingtheMiSeqReagentKitv3(2×250bppaired-endreads).

3.2.Sequencereadprocessing,OTUclusteringandtaxonomicassignments

Paired-endsequencesweremergedandtrimmedasdescribedpreviously[5].Dataweresub- sequentlyimportedintotheFROGS(FindRapidlyOTUswithGalaxySolution)pipeline[6]tobe cleaned,ﬁltered, clusteredintoOperationalTaxonomicunitsandtaxonomically assignedusing theSilva128SSUdatabase[7]andahomemadegyrBdatabase[5].

3.3.Sensorydescriptiveanalysis

Samplesofpoultryandporksausages,previouslystoredat−20°C,wereone-nightdefrostin acoldroom. Justbeforeanalysis, about50g ofsampleweretransferred intoa250mLopaque glassvial and sealedwith a glass stopper. Asensory panel of expertsin proﬁling techniques (n=15;atleast5previousexperiencesonfoodsensoryanalysiswithproﬁlingtechniques)were

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trainedduring8months(minimum15h)onalteredporkandpoultrysausages.Duringtraining, they developedaconsensus vocabularyinordertoseparateimportantattributesdescribingal- teredsausagesoff-odorcomparedtonon-alteredones.Sameattributeswerechosenforporkand poultrysausages.Quantitative descriptive analysis(QDA)[8]wasperformedusingthose seven olfactoryattributes.Thedifferentattributesandtheirrespectivedescriptorsusedfortheevalua- tionofthesampleswereglobalalterationodor,rancid,eggy/sulfurous,ethereal/fermentedfruit, fermented/old drysausage,old cheese,sour/pungent. TheQDAwasperformedintensessions.

Eachpanelistreceivedrandomly12codedsamplesinasession.Sampleswerepresentedmonad- icallyaccordingtoabalanceddesigninvialscontainingsausageforsniﬃng.Sensory evaluation wascarriedoutatroomtemperature(25±2°C)inisolatedboothsinasensorylab.Eachpanelist ratedtheglobalalterationodorintensityandthe6odorattributesintensitiesofeachsampleon a10cmunstructuredlinescale(from“absent” to“very intense”)withsensoryevaluationsoft- ware(FizzBiosystems,France).

3.4. Volatileorganiccompound(VOC)analysis

Samplesofpoultryandporksausages,previouslystoredat−20°C,werecutinsmallpiecesin acoldroomtominimizethevolatilizationofVOC.Around3–4gofsampleweretransferredinto a 20mL headspacevialandsealedwithascrewcap withsilicone rubberseptum.The vialwas weightedbefore and aftersamplingto determine the exactweight of sausage.Analyses were carriedoutintriplicate.VOCweredeterminedbyHS–GC–MS.Allanalyseswereperformedona Varian450gaschromatograph(Varian,USA)coupledtoaVarian225-ITmassspectrometer(Var- ian),equippedwithaCTCCombiPAL(CTCAnalyticsAG,Switzerland).Sampleswereequilibrated byagitationat60°Cfor20minpriortoinjectionand1mLwasdrawledfromtheheadspaceto injectintheGC.TheHS-GC–MSconditionswereasfollows:capillarycolumn:DB-624UI(30m x 0.25mm I.D×1.4mm film thickness) (Agilent Technologies, USA); Carrier gas: Helium with a flow rateof 1.4mL.min⁻¹; Injection port mode: splitless; Needle temperature: 60°C; Injec- tion temperature:220°C.The oven temperaturewasprogrammed froman initialtemperature of40°C(7minholding), risingto50°Cat4°C/min (1minholding), to70°Cat4°C/min(1min holding),to120°Cat3°C/min(2minholding)andto245°Cat30°C/min(4minholding).Trans- ferlinetemperature:250°C.Thetemperaturesofthemanifoldandtheiontrapwerekeptcon- stantat150°Cand40°Crespectively. Datawere obtainedinscan mode atfour scans/sinthe mass range(m/z) of35–350 atomicmass units.VOCwere identified by comparisonofGCre- tentiontimesandmassspectrawiththoseofthestandard compounds.Peakarea (inUA) was usedasquantitativedatatomonitortherelativechangesofVOCoverstorage,potassiumlactate concentration andatmospherepackaging. Datawere initiallysubjectedtopre-processingusing thestandardnormalvariatetransformationtofacilitatecomparisonofthepeakswithdifferent magnitudes.

ConﬂictofInterest

The authorsdeclarethat they havenoknown competingﬁnancialinterests orpersonal re- lationships which have, or could be perceived to have, inﬂuenced the work reported in this article. This work was supported by the ANR RedLosses Project, Grant ANR-16-CE21-0006, operated by the French Agence Nationale de la Recherche. SP and NDML were granted for postdoctoral and PhDstudy respectively through this agency. The funding body didnot play any role neither in the design of the study nor in collection, analysis, and interpretation of data.

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8 S. Poirier, N.-D.M. Luong and V. Anthoine et al. / Data in Brief 30 (2020) 105453 Acknowledgments

The authors express their gratitude to the INRAE MIGALE bioinformatics facility (MIGALE, INRAE,2020.MigalebioinformaticsFacility,doi:10.15454/1.5572390655343293E12)forproviding computationalresourcesanddatastorage.

Supplementarymaterials

Supplementarymaterial associated withthisarticlecan be found,inthe onlineversion, at doi:10.1016/j.dib.2020.105453.

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